Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
The dynamics of viral marketing
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
A Convergent Incremental Gradient Method with a Constant Step Size
SIAM Journal on Optimization
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Robust Stochastic Approximation Approach to Stochastic Programming
SIAM Journal on Optimization
Kronecker Graphs: An Approach to Modeling Networks
The Journal of Machine Learning Research
Inferring networks of diffusion and influence
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Modeling Information Diffusion in Implicit Networks
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Patterns of temporal variation in online media
Proceedings of the fourth ACM international conference on Web search and data mining
Proceedings of the 20th international conference on World wide web
Refining causality: who copied from whom?
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Winner takes all: competing viruses or ideas on fair-play networks
Proceedings of the 21st international conference on World Wide Web
Information diffusion and external influence in networks
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Clash of the Contagions: Cooperation and Competition in Information Diffusion
ICDM '12 Proceedings of the 2012 IEEE 12th International Conference on Data Mining
Information diffusion in online social networks
Proceedings of the 2013 Sigmod/PODS Ph.D. symposium on PhD symposium
Discovering latent influence in online social activities via shared cascade poisson processes
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Cascading outbreak prediction in networks: a data-driven approach
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
The social media genome: modeling individual topic-specific behavior in social media
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Information diffusion in online social networks: a survey
ACM SIGMOD Record
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Diffusion of information, spread of rumors and infectious diseases are all instances of stochastic processes that occur over the edges of an underlying network. Many times networks over which contagions spread are unobserved, and such networks are often dynamic and change over time. In this paper, we investigate the problem of inferring dynamic networks based on information diffusion data. We assume there is an unobserved dynamic network that changes over time, while we observe the results of a dynamic process spreading over the edges of the network. The task then is to infer the edges and the dynamics of the underlying network. We develop an on-line algorithm that relies on stochastic convex optimization to efficiently solve the dynamic network inference problem. We apply our algorithm to information diffusion among 3.3 million mainstream media and blog sites and experiment with more than 179 million different pieces of information spreading over the network in a one year period. We study the evolution of information pathways in the online media space and find interesting insights. Information pathways for general recurrent topics are more stable across time than for on-going news events. Clusters of news media sites and blogs often emerge and vanish in matter of days for on-going news events. Major social movements and events involving civil population, such as the Libyan'{}s civil war or Syria'{}s uprise, lead to an increased amount of information pathways among blogs as well as in the overall increase in the network centrality of blogs and social media sites.